A question answer system answers questions posed in a natural language format by applying advanced natural language processing, information retrieval, knowledge representation, automated reasoning, and machine learning technologies. Question answer systems differ from typical document search technologies because document search technologies return a list of documents ranked in order of relevance to a word query, whereas a question answer system receives a question expressed in a natural language, analyzes the question in a natural language context, and returns a precise answer to the question.
To prepare a question answer system to receive questions and provide precise answers, software developers train the question answer system to specific domains such as a financial domain, a travel domain, a medical domain, etc. During the training process, the question answer system ingests a corpus of documents from trusted, traditional sources (textbooks, journals) that include accurate information. During document ingestion, the question answer system uses annotators to add annotations to the document that the question answer system eventually utilizes to identify and return precise answers to questions.